Triple

T460294
Position Surface form Disambiguated ID Type / Status
Subject British American Tobacco E7321 entity
Predicate brand P1500 FINISHED
Object Kent E5977 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kent | Statement: [British American Tobacco, brand, Kent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kent
Context triple: [British American Tobacco, brand, Kent]
  • A. Kent chosen
    Kent is a county in southeastern England known for its historic towns, coastal landscapes, and nickname "the Garden of England."
  • B. York
    York is a historic former municipality in Ontario, Canada, that is now part of the modern city of Toronto.
  • C. York
    York is a historic walled city in North Yorkshire, England, renowned for its medieval architecture, including York Minster, and its rich Roman and Viking heritage.
  • D. Derbyshire
    Derbyshire is a county in the East Midlands of England known for its rural landscapes, historic market towns, and much of the Peak District National Park.
  • E. Kentucky
    Kentucky is a southeastern U.S. state known for its horse racing, bourbon distilleries, bluegrass music, and diverse landscapes ranging from Appalachian mountains to fertile river valleys.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a2e7e5c5bc8190a1dc8178218fba40 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2efbd6ed481909ec40f12b5b675c8 completed Feb. 28, 2026, 1:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69a44f583ea081908d92fe5b5dc4d3c0 completed March 1, 2026, 2:38 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.